Enhancing Emotional Intelligence Through Generative AI‐Supported Digital Storytelling: A Mixed Methods Study Using Epistemic Network Analysis.

Background: Social–emotional learning (SEL) has gained increasing attention in recent years due to its importance for students' emotional regulation, motivation and learning engagement. Digital storytelling (DST) has been widely recognised as a promising approach for supporting SEL; however, student...

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Publicado en:Journal of Computer Assisted Learning Vol. 42; no. 3; pp. 1 - 19
Autores principales: Hwang, Gwo‐Jen, Tu, Yun‐Fang, Lin, Yue‐I, Chen, Hsiu‐Ling
Formato: pictorial research tables/charts randomized controlled trial Journal Article
Publicado: Wiley-Blackwell Jun2026
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Jun2026
      vid: 42
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      pub: Wiley-Blackwell
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        10.1002/jcal.70245
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        atl: Enhancing Emotional Intelligence Through Generative AI‐Supported Digital Storytelling: A Mixed Methods Study Using Epistemic Network Analysis.
      aug:
        au:
          Hwang, Gwo‐Jen
          Tu, Yun‐Fang
          Lin, Yue‐I
          Chen, Hsiu‐Ling
        affil: Graduate Institute of Educational Information and Measurement, National Taichung University of Education, Taichung, Taiwan
      sug:
        subj:
          Emotional Intelligence Education
          Artificial Intelligence, Generative Utilization
          Digital Technology
          Storytelling
          Learning Methods
          Outcomes of Education
          Students, Middle School
          Human
          Male
          Female
          Taiwan
          Multimethod Studies
          Quasi-Experimental Studies
          Randomized Controlled Trials
          Random Assignment
          Epistemology
          Self-Efficacy
          Descriptive Statistics
          Pretest-Posttest Control Group Design
          Semi-Structured Interview
          Student Attitudes
          Cognition
          Emotions
          Motivation
          Problem Solving
          Skill Acquisition
          Teachers
          Job Experience
          Self Regulation
          Self-Awareness
          Empathy
          Unpaired T-Tests
          Analysis of Covariance
          Grounded Theory
          Data Analysis Software
          Mann-Whitney U Test
          Male
          Female
      ab: Background: Social–emotional learning (SEL) has gained increasing attention in recent years due to its importance for students' emotional regulation, motivation and learning engagement. Digital storytelling (DST) has been widely recognised as a promising approach for supporting SEL; however, students often encounter challenges related to creative expression and technical execution during the storytelling process. Objective: Although DST holds considerable promise for supporting SEL, students often encounter challenges related to creative expression when using DST, which may limit their learning effectiveness. To address this issue, this study proposed a generative‐AI (GAI)‐supported DST approach. Method: A quasi‐experimental design was adopted with 62 junior high school students. The experimental group (n = 30) learned using the GAI‐DST approach, while the control group (n = 32) adopted a conventional DST approach. Quantitative data were collected through pre‐ and post‐questionnaires on emotional intelligence and self‐efficacy. Qualitative interview data were further analysed using epistemic network analysis (ENA) to explore students' learning perceptions and cognitive‐emotional patterns. Results and Conclusions: Results showed that the GAI‐DST approach significantly enhanced students' self‐efficacy and the motivation dimension of emotional intelligence, while no significant differences were found in other emotional intelligence dimensions. The qualitative findings revealed that students in the GAI‐DST group demonstrated a stronger orientation towards practice‐based learning, tool‐supported problem solving and emotional engagement, whereas students in the control group focused more on mastering basic skills. These findings suggest that the GAI‐DST approach may exert selective effects on motivational and self‐efficacy‐related processes, rather than producing immediate, broad‐based improvements across all dimensions of emotional intelligence. By conceptualising GAI as a mediational learning tool that supports mastery experiences and reflective interaction, this study provides a theoretically grounded explanation of how GAI can support SEL and offers suggestions for the design of AI‐integrated instructional activities. Lay Description: What is already known about this topic ○Social–emotional learning (SEL) has been increasingly recognised for its importance in enhancing students' emotional intelligence and self‐efficacy.○Digital storytelling (DST) integrates technology with traditional narrative techniques to boost student engagement and learning interest. However, students often face technological and creative challenges when using DST, which may hinder learning effectiveness.○The emergence of generative artificial intelligence (GAI) offers potential solutions to these challenges by assisting students in overcoming technological and creative barriers and improving the quality of their DST work.What this paper adds ○This study proposes a GAI‐supported DST approach to prompting students' emotional intelligence.○An experiment was conducted to compare the effects of the GAI‐DST and conventional DST (C‐DST) learning approaches on students' self‐efficacy, emotional intelligence and learning perceptions using mixed methods, including epistemic network analysis.○Results show that the GAI‐DST approach significantly enhanced students' self‐efficacy and the motivation dimension of emotional intelligence. It also shifted students' focus towards practice‐oriented learning, emphasising the practical application of knowledge and emotional connection.Implications for practice and/or policy ○Findings suggest that GAI‐assisted DST can provide students with greater opportunities for practice‐oriented, emotionally connected learning, which may lead to more meaningful educational experiences.○This study offers insights for future research and SEL curriculum design.
      pubtype: Academic Journal
      doctype:
        pictorial
        research
        tables/charts
        randomized controlled trial
        Journal Article
      ougenre: Article
    language: English
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